Characterization of Brown Adipose Tissue in a Diabetic Mouse Model with Spiral Volumetric Optoacoustic Tomography

PURPOSE Diabetes is associated with a deterioration of the microvasculature in brown adipose tissue (BAT) and with a decrease in its metabolic activity. Multispectral optoacoustic tomography has been recently proposed as a new tool capable of differentiating healthy and diabetic BAT by observing hemoglobin gradients and microvasculature density in cross-sectional (2D) views. We report on the use of spiral volumetric optoacoustic tomography (SVOT) for an improved characterization of BAT. PROCEDURES A streptozotocin-induced diabetes model and control mice were scanned with SVOT. Volumetric oxygen saturation (sO) as well as total blood volume (TBV) in the subcutaneous interscapular BAT (iBAT) was quantified. Segmentation further enabled separating feeding and draining vessels from the BAT anatomical structure. RESULTS Scanning revealed a 46 % decrease in TBV and a 25 % decrease in sO in the diabetic iBAT with respect to the healthy control. CONCLUSIONS These results suggest that SVOT may serve as an effective tool for studying the effects of diabetes on BAT. The volumetric optoacoustic imaging probe used for the SVOT scans can be operated in a handheld mode, thus potentially providing a clinical translation route for BAT-related studies with this imaging technology

Volumetric Optoacoustic Imaging Unveils High-Resolution Patterns of Acute and Cyclic Hypoxia in a Murine Model of Breast Cancer

Mapping tumor heterogeneity and hypoxia within a living intact organism is essential for understanding the processes involved in cancer progression and assessing long-term responses to therapies. Efficient investigations into tumor hypoxia mechanisms have been hindered by the lack of intravital imaging tools capable of multiparametric probing of entire solid tumors with high spatial and temporal resolution. Here, we exploit volumetric multispectral optoacoustic tomography (vMSOT) for accurate, label-free delineation of tumor heterogeneity and dynamic oxygenation behavior. Mice bearing orthotopic MDA-MB-231 breast cancer xenografts were imaged noninvasively during rest and oxygen stress challenge, attaining time-lapse three-dimensional oxygenation maps across entire tumors with 100 μm spatial resolution. Volumetric quantification of the hypoxic fraction rendered values of 3.9% to 21.2%, whereas the oxygen saturation (sO2) rate declined at 1.7% to 2.3% per mm in all tumors when approaching their core. Three distinct functional areas (the rim, hypoxic, and normoxic cores) were clearly discernible based on spatial sO2 profiles and responses to oxygen challenge. Notably, although sO2 readings were responsive to the challenge, deoxyhemoglobin (HbR) trends exhibited little to no variations in all mice. Dynamic analysis further revealed the presence of cyclic hypoxia patterns with a 21% average discrepancy between cyclic fractions assessed via sO2 (42.2% ± 17.3%) and HbR fluctuations (63% ± 14.1%) within the hypoxic core. These findings corroborate the strong potential of vMSOT for advancing preclinical imaging of cancer and informing clinical decisions on therapeutic interventions

Self-Gated Respiratory Motion Rejection for Optoacoustic Tomography

Respiratory motion in living organisms is known to result in image blurring and loss of resolution, chiefly due to the lengthy acquisition times of the corresponding image acquisition methods. Optoacoustic tomography can effectively eliminate in vivo motion artifacts due to its inherent capacity for collecting image data from the entire imaged region following a single nanoseconds-duration laser pulse. However, multi-frame image analysis is often essential in applications relying on spectroscopic data acquisition or for scanning-based systems. Thereby, efficient methods to correct for image distortions due to motion are imperative. Herein, we demonstrate that efficient motion rejection in optoacoustic tomography can readily be accomplished by frame clustering during image acquisition, thus averting excessive data acquisition and post-processing. The algorithm’s efficiency for two- and three-dimensional imaging was validated with experimental whole-body mouse data acquired by spiral volumetric optoacoustic tomography (SVOT) and full-ring cross-sectional imaging scanners

Self-Gated Respiratory Motion Rejection for Optoacoustic Tomography

Respiratory motion in living organisms is known to result in image blurring and loss of resolution, chiefly due to the lengthy acquisition times of the corresponding image acquisition methods. Optoacoustic tomography can effectively eliminate in vivo motion artifacts due to its inherent capacity for collecting image data from the entire imaged region following a single nanoseconds-duration laser pulse. However, multi-frame image analysis is often essential in applications relying on spectroscopic data acquisition or for scanning-based systems. Thereby, efficient methods to correct for image distortions due to motion are imperative. Herein, we demonstrate that efficient motion rejection in optoacoustic tomography can readily be accomplished by frame clustering during image acquisition, thus averting excessive data acquisition and post-processing. The algorithm’s efficiency for two- and three-dimensional imaging was validated with experimental whole-body mouse data acquired by spiral volumetric optoacoustic tomography (SVOT) and full-ring cross-sectional imaging scanners.ISSN:2076-341

Optoacoustic properties of Doxorubicin - A pilot study

Doxorubicin (DOX) is a widely used chemotherapeutic anticancer drug. Its intrinsic fluorescence properties enable investigation of tumor response, drug distribution and metabolism. First phantom studies in vitro showed optoacoustic property of DOX. We therefore aimed to further investigate the optoacoustic properties of DOX in biological tissue in order to explore its potential as theranostic agent. We analysed doxorubicin hydrochloride (Dox·HCl) and liposomal encapsulated doxorubicin hydrochloride (Dox·Lipo), two common drugs for anti-cancer treatment in clinical medicine. Optoacoustic measurements revealed a strong signal of both doxorubicin substrates at 488 nm excitation wavelength. Post mortem analysis of intra-tumoral injections of DOX revealed a detectable optoacoustic signal even at three days after the injection. We thereby demonstrate the general feasibility of doxorubicin detection in biological tissue by means of optoacoustic tomography, which could be applied for high resolution imaging at mesoscopic depths dictated by effective penetration of visible light into the biological tissues

Optoacoustic properties of Doxorubicin – A pilot study

Doxorubicin (DOX) is a widely used chemotherapeutic anticancer drug. Its intrinsic fluorescence properties enable investigation of tumor response, drug distribution and metabolism. First phantom studies in vitro showed optoacoustic property of DOX. We therefore aimed to further investigate the optoacoustic properties of DOX in biological tissue in order to explore its potential as theranostic agent. We analysed doxorubicin hydrochloride (Dox·HCl) and liposomal encapsulated doxorubicin hydrochloride (Dox·Lipo), two common drugs for anti-cancer treatment in clinical medicine. Optoacoustic measurements revealed a strong signal of both doxorubicin substrates at 488 nm excitation wavelength. Post mortem analysis of intra-tumoral injections of DOX revealed a detectable optoacoustic signal even at three days after the injection. We thereby demonstrate the general feasibility of doxorubicin detection in biological tissue by means of optoacoustic tomography, which could be applied for high resolution imaging at mesoscopic depths dictated by effective penetration of visible light into the biological tissues

Validity of machine learning in biology and medicine increased through collaborations across fields of expertise

Machine learning (ML) has become an essential asset for the life sciences and medicine. We selected 250 articles describing ML applications from 17 journals sampling 26 different fields between 2011 and 2016. Independent evaluation by two readers highlighted three results. First, only half of the articles shared software, 64% shared data and 81% applied any kind of evaluation. Although crucial for ensuring the validity of ML applications, these aspects were met more by publications in lower-ranked journals. Second, the authors’ scientific backgrounds highly influenced how technical aspects were addressed: reproducibility and computational evaluation methods were more prominent with computational co-authors; experimental proofs more with experimentalists. Third, 73% of the ML applications resulted from interdisciplinary collaborations comprising authors from at least two of the three disciplines: computational sciences, biology, and medicine. The results suggested collaborations between computational and experimental scientists to generate more scientifically sound and impactful work integrating knowledge from both domains. Although scientifically more valid solutions and collaborations involving diverse expertise did not correlate with impact factors, such collaborations provide opportunities to both sides: computational scientists are given access to novel and challenging real-world biological data, increasing the scientific impact of their research, and experimentalists benefit from more in-depth computational analyses improving the technical correctness of work